Python で htsprophet パッケージを使用しようとしています。以下のサンプルコードを使用しています。この例は、https://github.com/CollinRooney12/htsprophet/blob/master/htsprophet/runHTS.pyから取得されます。私が得ている問題は ValueError"holidays must be a DataFrame with 'ds' and 'holiday' columnです。dsと休日の2つの列を持つデータフレームの休日が明らかにあるため、これを回避する方法があるかどうか疑問に思っています。エラーは、予測ファイルの fbprophet の依存パッケージの 1 つに起因すると考えられます。追加する必要があるものがあるかどうか、またはこれを修正するために誰かが何かを追加したかどうか疑問に思っています。
import pandas as pd
from htsprophet.hts import hts, orderHier, makeWeekly
from htsprophet.htsPlot import plotNode, plotChild, plotNodeComponents
import numpy as np
#%% Random data (Change this to whatever data you want)
date = pd.date_range("2015-04-02", "2017-07-17")
date = np.repeat(date, 10)
medium = ["Air", "Land", "Sea"]
businessMarket = ["Birmingham","Auburn","Evanston"]
platform = ["Stone Tablet","Car Phone"]
mediumDat = np.random.choice(medium, len(date))
busDat = np.random.choice(businessMarket, len(date))
platDat = np.random.choice(platform, len(date))
sessions = np.random.randint(1000,10000,size=(len(date),1))
data = pd.DataFrame(date, columns = ["day"])
data["medium"] = mediumDat
data["platform"] = platDat
data["businessMarket"] = busDat
data["sessions"] = sessions
#%% Run HTS
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# Make the daily data weekly (optional)
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data1 = makeWeekly(data)
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# Put the data in the format to run HTS, and get the nodes input (a list of list that describes the hierarchical structure)
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data2, nodes = orderHier(data, 1, 2, 3)
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# load in prophet inputs (Running HTS runs prophet, so all inputs should be gathered beforehand)
# Made up holiday data
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holidates = pd.date_range("12/25/2013","12/31/2017", freq = 'A')
holidays = pd.DataFrame(["Christmas"]*5, columns = ["holiday"])
holidays["ds"] = holidates
holidays["lower_window"] = [-4]*5
holidays["upper_window"] = [0]*5
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# Run hts with the CVselect function (this decides which hierarchical aggregation method to use based on minimum mean Mean Absolute Scaled Error)
# h (which is 12 here) - how many steps ahead you would like to forecast. If youre using daily data you don't have to specify freq.
#
# NOTE: CVselect takes a while, so if you want results in minutes instead of half-hours pick a different method
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myDict = hts(data2, 52, nodes, holidays = holidays, method = "FP", transform = "BoxCox")
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